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This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.

At first, the authors measured the responsiveness of the Indian automobile supply chain, encompassing the top ten major automobile manufacturers, using both sentiment and conjoint analysis. Second, the authors used data envelopment analysis to identify the frontiers of their supply chain. The authors also measured the supply chain's efficiency, using the balance sheet. Further, the authors analyzed the “strategic fit” zone and discussed the results.

The results indicate that both the proposed methods yield similar outcomes in terms of strategic fitment.

The study outcomes facilitate measuring the strategic fit, thereby leveraging the resources available to align. The methodology proposed is both easy to use and practice. The methodology eases time and costs by eliminating hiring agencies to appraise the strategic fit. This valuable method to measure strategic fit can be considered feedback for strategic actions. This methodology could also be incorporated possibly as an operative measurement and control tool.

Data triangulation meaningfully enhances the accuracy and reliability of the analyses of strategic fit. Data triangulation leads to actionable insights relevant to top managers and strategic positioning of top managers within a supply chain.

This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.

This study aims to examine the impact of board characteristics on climate change disclosures (CCDs) in the context of an emerging economy, with a unique focus on regulatory influences.

This study analyzes longitudinal data (2014–2021) from environmentally sensitive firms listed on the Dhaka Stock Exchange, using a disclosure index developed within the Global Reporting Initiative framework. The authors use a neo-institutional theoretical lens to explore regulatory influences on CCD through board characteristics. This study uses hand-collected data from annual reports owing to the absence of an established database.

The results indicate that a larger board size, the presence of foreign directors and the existence of an audit committee correlate with higher levels of CCD disclosure. Conversely, a higher frequency of board meetings is associated with lower CCD disclosure levels. This study also observed an increase in CCD following the implementation of corporate governance guidelines by the Bangladesh Securities and Exchange Commission, albeit with a relatively low number of firms making these disclosures.

This study contributes to the climate change reporting literature by providing empirical evidence of regulatory influences on CCD through board characteristics in an emerging economy. However, the findings may not be universally applicable, considering the study’s focus on Bangladeshi listed firms.

This study suggests growing pressures for diverse stakeholders, including researchers and regulatory bodies, to integrate climate change disclosure into routine activities. This study offers a valuable framework and insights for various stakeholders.

By emphasizing the influence of good governance and sustainability practices, this study contributes to stakeholders’ understanding, aiming to contribute to a better world.

This study stands out by uniquely positioning itself in the climate change reporting literature, shedding light on regulatory influences on CCD through board characteristics in the context of an emerging economy.

A parabolic trough solar collector is an advanced concentrated solar power technology that significantly captures radiant energy. Solar power will help different sectors reach their energy needs in areas where traditional fuels are in use. This study aims to examine the sensitivity analysis for optimizing the heat transfer and entropy generation in the Jeffrey magnetohydrodynamic hybrid nanofluid flow under the influence of motile gyrotactic microorganisms with solar radiation in the parabolic trough solar collectors. The influences of viscous dissipation and Ohmic heating are also considered in this investigation.

Governing partial differential equations are derived via boundary layer assumptions and nondimensionalized with the help of suitable similarity transformations. The resulting higher-order coupled ordinary differential equations are numerically investigated using the Runga-Kutta fourth-order numerical approach with the shooting technique in the computational MATLAB tool.

The numerical outcomes of influential parameters are presented graphically for velocity, temperature, entropy generation, Bejan number, drag coefficient and Nusselt number. It is observed that escalating the values of melting heat parameter and the Prandl number enhances the Nusselt number, while reverse effect is observed with an enhancement in the magnetic field parameter and bioconvection Lewis number. Increasing the magnetic field and bioconvection diffusion parameter improves the entropy and Bejan number.

Nanotechnology has captured the interest of researchers due to its engrossing performance and wide range of applications in heat transfer and solar energy storage. There are numerous advantages of hybrid nanofluids over traditional heat transfer fluids. In addition, the upswing suspension of the motile gyrotactic microorganisms improves the hybrid nanofluid stability, enhancing the performance of the solar collector. The use of solar energy reduces the industry’s dependency on fossil fuels.

In the swiftly evolving business landscape, environmental, social and governance (ESG) considerations have gained exceptional prominence, as stakeholders increasingly emphasize accountability and sustainability. This study aims to meticulously probe the intricate interplay between ESG factors, financial performance and the distinct corporate governance landscape that characterizes the Nordic region's crucible of proactive societal and environmental commitment.

The authors begin with a data set of 899 Nordic firms across Sweden, Norway, Denmark, Finland and Iceland. Using the Thomson Reuters database, they refine this data set by excluding non-regional headquarters and entities without ESG scores or year-long financial data. This resulted in a focused data set of 1,360 firm-years spanning a decade, forming the foundation for investigating the link between ESG factors and financial performance in Nordic firms.

Drawing upon empirical data, the authors systematically dissect the correlation between specified financial ratios and ESG scores on the bedrock of sustainability evaluation. The findings underscore a partially significant, yet robust relationship between ESG endeavors and financial performance metrics. Furthermore, the intricate interplay of corporate governance dimensions’ reveals intriguing correlations with financial indicators among the surveyed Nordic enterprises. However, the findings also reveal an intricate weave that underscores the ESG and financial performance nexus.

This study addresses stakeholders’ theory and unique positions and contributes to the current discussion on sustainability reporting literature by providing empirical evidence of ESG influences on firm profitability through board characteristics in the specific context of the Nordic region. The sample for this study encompasses firms listed in Nordic countries; thus, the results may not be generalizable to unlisted firms and other countries or regions.

This study suggests that Nordic firms are advanced in reporting ESG in response to diverse stakeholder demands as part of their regular activities. This study provides valuable insights for diverse stakeholders including researchers and regulatory bodies.

This study provides an understanding of stakeholders about the association of ESG and sustainability practices with firm profitability, which might lead to making the world a better place.

While illuminating the multifaceted ESG-financial performance nexus, this study reveals its intricate nature. This complexity accentuates the compelling need for further exploration to decode the exact outcomes and myriad factors contributing to the array of correlations observed. Through this comprehensive inquiry, this research advances the understanding and underscores the pivotal role of a focused investigation. This study seeks to harmonize ESG practices and financial performance seamlessly within the Nordic business realm.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.

A progressive hybrid censoring scheme (PHCS) becomes impractical for ensuring dependable outcomes when there is a low likelihood of encountering a small number of failures prior to the predetermined terminal time T. The generalized progressive hybrid censoring scheme (GPHCS) efficiently addresses to overcome the limitation of the PHCS.

In this article, estimation of model parameter, survival and hazard rate of the Unit-Lindley distribution (ULD), when sample comes from the GPHCS, have been taken into account. The maximum likelihood estimator has been derived using Newton–Raphson iterative procedures. Approximate confidence intervals of the model parameter and their arbitrary functions are established by the Fisher information matrix. Bayesian estimation procedures have been derived using Metropolis–Hastings algorithm under squared error loss function. Convergence of Markov chain Monte Carlo (MCMC) samples has been examined. Various optimality criteria have been considered. An extensive Monte Carlo simulation analysis has been shown to compare and validating of the proposed estimation techniques.

The Bayesian MCMC approach to estimate the model parameters and reliability characteristics of the generalized progressive hybrid censored data of ULD is recommended. The authors anticipate that health data analysts and reliability professionals will get benefit from the findings and approaches presented in this study.

The ULD has a broad range of practical utility, making it a problem to estimate the model parameters as well as reliability characteristics and the significance of the GPHCS also encourage the authors to consider the present estimation problem because it has not previously been discussed in the literature.

The purpose of this paper is to design a cascaded Multilevel inverter with reduce number of switches for high power applications. This paper came up with an innovative three-phase multilevel inverter (MLI) topology, which is a cascaded structure based on classical three-legged voltage source inverter (VSI) bridges as an individual module. The prominent advantage of this topology is that it requires only one direct current (DC) link system. The main characteristic of it is that a higher number of voltage levels can be achieved with considerably a smaller number of semiconductor switches, which improves the reliability, power quality, cost and size of the system significantly.

The individual modules are cascaded through three-phase transformers to provide higher voltage at the output with the higher number of voltage levels. In this work, the phase-shifted pulse width modulation technique is implemented to verify the result.

The proposed topology is compared with three-phase cascaded H-bridge MLI (CHB-MLI) and a modified CHB-MLI topology and found better in many aspects. The proposed MLI can produce a higher number of voltage levels with fewer semiconductor switches and associated triggering circuitry. As the device count in the proposed MLI is less compared to other MLI discussed, it tends to have less switching and conduction loss which increases the efficiency and reliability. As the number of level increases, the voltage profile and the total harmonic distortion of the proposed MLI improves.

This is a transformer-based modular cascaded MLI, which is based on classical VSI bridges. Here in this topology, a single module provides all three phases. So, a single string of cascaded modules is enough for three-phase multilevel voltage generation.

The demand for over-the-top (OTT) video streaming services has grown manifold in the last few years. With increasing competition in the OTT market, it is vitally important for businesses to understand OTT retail consumers' continuance intentions. This study aims to understand the antecedents of the continuance intention of OTT platforms and distinguish the most essential and best-performing predictor variables of continuance intention.

The study employs an integrated research model based on the theory of planned behavior (TPB), flow theory and habit. Data collected from OTT retail consumers (n = 383) using the online survey method are analyzed using partial least squares structural equation modeling.

The results elucidated which TPB antecedents and dimensions of flow experience affect OTT platforms' continuance intention. The most important factors affecting continuance intention were habit, attitude and perceived behavioral control, while the best-performing factors were perceived behavioral control, perceived enjoyment and attitude.

The study is unique in harmoniously integrating conscious cognitive intention, intrinsic motivation and habit of performing an activity to explain OTT platforms' continuance intention.

This study assesses the SDG-related well-being of indigenous communities in India using bibliometric analysis and the ADO-TCM framework. It provides insights into their alignment with sustainable development objectives.

This study analysed 74 high-impact journals using bibliometric analysis to evaluate the well-being of India’s indigenous peoples about the SDGs.

This study analyses the well-being of tribal communities in India using existing scholarly articles and the ADO-TCM framework. It emphasises the importance of implementing Sustainable Development Goals (SDGs) to promote the well-being of indigenous populations.

This study uses bibliometric analysis and the ADO-TCM framework to investigate factors impacting tribal community welfare. It proposes theoretical frameworks, contextual considerations and research methodologies to achieve objectives.